RESUMO
For the effectiveness of a computer-aided diagnosis system, the quality of whole-slide image (WSI) is the foundation, and a useful autofocus method is an important part of ensuring the quality of WSI. The existing autofocus methods need to balance focusing speed and focusing accuracy, and need to be optimized separately for different samples or scenes. In this paper, a robust autofocus method based on fiber bundle illumination and image normalization analysis is proposed. For various application scenes, it meets the requirements of autofocusing through active illumination, such as bright field imaging and fluorescence imaging. For different structures on samples, it ensures the autofocusing accuracy through image analysis. The experimental results imply that the autofocusing method in this paper can effectively track the change of the distance from the sample to the focal plane and significantly improve the WSI quality.
RESUMO
Quantifying the resolution of a super-resolution image is vital for biologists trying to apply super-resolution microscopy in various research fields. Among the reported image resolution estimation methods, the one that calculates the full width at half maximum (FWHM) of line profile, called FWHM resolution, continues the traditional resolution criteria and has been popularly used by many researchers. However, quantifying the FWHM resolution of a super-resolution image is a time-consuming, labor-intensive, and error-prone process because this method typically involves a manual and careful selection of one or several of the smallest structures. In this paper, we investigate the influencing factors in FWHM resolution quantification systematically and present an ImageJ plug-in called LuckyProfiler for biologists so that they can have an easy and effective way of quantifying the FWHM resolution of super-resolution images.
